This is the internal function upon which the iceberg
wrapper is built. It performs standard
plugin lasso PPML estimation without fixed effects, relying on glmnet::glmnet
. As the other
internals in the package, it needs a y vector and an x matrix.
plugin_lasso_int(
y,
x,
tol = 1e-08,
glmnettol = 1e-12,
penweights = NULL,
colcheck = FALSE,
K = 50,
verbose = FALSE,
lambda = NULL,
icepost = FALSE
)
A list with 14 elements, including beta
, which is the only one we use in the wrapper.
For a full list, see glmnet.
Dependent variable (a vector).
Regressor matrix.
Tolerance parameter for convergence of the IRLS algorithm.
Tolerance parameter to be passed on to glmnet::glmnet
.
Optional: a vector of coefficient-specific penalties to use in plugin lasso.
Logical. If TRUE
, checks for perfect multicollinearity in x
.
Maximum number of iterations.
Logical. If TRUE
, prints information to the screen while evaluating.
Penalty parameter (a number).
Logical. If TRUE
, it carries out a post-lasso estimation with just the
selected variables and reports the coefficients from this regression.